The 2016 Phenom Index for Rookie Wide Receivers

In the two years since the introduction of the Phenom Index, the intersection of age and production has gained more traction in the NFL Draft community. Thanks to everyone who has built on this work and done additional research on age factors. Here is the 2016 edition of the Phenom Index for wide receivers.

To be perfectly clear, introducing age into the equation doesn’t mean older prospects can’t be good; it just means that expectations are different for older players. After all, the age range of draft-eligible receivers in 2016 spans from 20.4 to 25.4, so doesn’t it make sense that we have a way to adjust for their age? The Phenom Index is my way of doing that.


The scores below represent what a player accomplished and at what age, in their final college season. I then bolted the numbers together using z-scores, as described last year, to create this score. Other than this number and where a player gets drafted, not much else matters in predicting a player’s early career NFL success. Sometimes physical measures like weight and vertical jump show up. Collegiate special teams performance matters too, but not much else.

Since I’m sure somebody will ask “what’s the threshold for predicting an elite prospect,” I want to suggest that there isn’t a threshold, but rather to stay focused players who were above average from an age/production perspective in their final college season. These guys will have a score greater than zero. It’s pretty rare for a player to be below average in their final college season and then have NFL success. It’s happened a few times since 2004, but it’s rare. This paradigm isn’t going to get everyone right, but it’s going to help allocate your draft time most efficiently and identify the highest upside prospects. And as a reminder, draft position (opportunity) matters a lot.

For what it’s worth, here is some data about the Phenom scores for the top 12 fantasy receivers from the 2015 NFL season, which might help guide your thinking. These are the Antonio BrownAllen RobinsonDeAndre Hopkins-types. In parenthesis, I’ve included what these figures were in last year’s article,1 so you can see that these marks are holding steady.

  • Lowest PI score in cohort of top 12 receivers: 0.22 – Doug Baldwin  (0.67 – E. Sanders)
  • Median PI score in cohort of top 12 receivers: 2.20  (2.07)
  • Average PI score in cohort of top 12 receivers: 2.47  (2.24)
  • Highest PI score in cohort of top 12 receivers: 4.44 – Allen Robinson  (4.2 – D. Thomas)


I’ve sorted the table to display the top 20 scores for the 2016 WR class, but there are nearly 130 total scores included below for you to explore. Also, because combine invites seem to matter, I’ve indicated that. If you want to check out historical scores, there were nearly 800 published in the 2015 edition of this article.

WRDraftCollegeCombine?msYDSMSyd ZAgeAge ZPhenom
Tajae Sharpe2016MassachusettsYES42.71.5621-1.653.2
Pharoh Cooper2016South CarolinaYES39.11.2220.8-1.883.1
Tyler Boyd2016PittsburghYES39.51.2621.2-1.52.75
Rashard Higgins2016Colorado StateYES37.61.0821.2-1.412.49
Leonte Carroo2016RutgersYES43.61.6421.9-0.622.26
Laquon Treadwell2016Ole MissYES26.50.0420.5-2.182.22
Corey Coleman2016BaylorYES37.31.0521.5-1.112.17
Demarcus Ayers2016HoustonYES35.10.8521.5-1.131.98
Will Fuller2016Notre DameYES37.41.0721.7-0.881.94
Hunter Sharp2016Utah StateYES36.50.9821.7-0.911.88
Jalin Marshall2016Ohio StateYES21.3-0.4420.4-2.291.85
Michael Thomas SM2016Southern Mississippi320.5621.4-1.251.81
Jordan Williams2016Ball State35.10.8521.6-0.951.8
Thomas Duarte2016UCLAYES23.3-0.2620.8-1.951.69
Aaron Burbridge2016Michigan StateYES38.41.1522-0.531.68
Paul McRoberts2016Southeast Missouri State49.52.1923.10.711.48
Carlos Harris2016North Texas37.51.0822.1-0.391.46
Jenson Stoshak2016Florida Atlantic32.10.5621.8-0.831.39
Ricardo Louis2016AuburnYES31.70.5321.8-0.811.34
Daniel Braverman2016Western Michigan36.7122.3-0.261.26
Michael Thomas OSU2016Ohio StateYES31.80.5421.8-0.7431.28
Imani Davis2016Akron27.10.121.5-1.081.18
Dezmon Epps2016Idaho47.21.9823.40.971.01
Geronimo Allison2016IllinoisYES30.20.3922-0.60.99
De'Runnya Wilson2016Mississippi StateYES22.3-0.3521.3-1.340.99
Malcolm Mitchell2016GeorgiaYES360.9322.4-0.050.98
Dennis Parks2016Rice23.1-0.2721.4-1.190.92
KJ Maye2016Minnesota27.70.1521.9-0.720.87
Roger Lewis2016Bowling GreenYES30.10.3822.1-0.440.82
Demarcus Robinson2016FloridaYES19.8-0.5921.3-1.360.77
Daje Johnson2016Texas24.5-0.1521.7-0.890.74
Jaydon Mickens2016Washington22.3-0.3521.7-0.890.54
Rashon Ceaser2016Louisiana-Monroe31.20.4822.5-0.030.51
Jordan Payton2016UCLAYES29.50.3322.3-0.180.5
Jehu Chesson2016Michigan24.7-0.1222-0.540.42
Max McCaffrey2016Duke20.1-0.5621.6-0.970.42
Amara Darboh2016Michigan23.5-0.2321.9-0.640.41
Teddy Ruben2016Troy30.40.4122.50.010.4
Marquez North2016TennesseeYES8-1.6920.7-2.010.32
Devin Lucien2016Arizona State29.80.3522.50.030.32
Bryce Treggs2016California19.5-0.6121.7-0.920.32
Robby Anderson2016Temple30.90.4622.60.170.28
Marcus Johnson2016Texas15.8-0.9521.4-1.220.26
Malachi Jones2016Appalachian State19.8-0.5921.8-0.80.21
Josh Doctson2016TCUYES35.20.8623.10.660.2
Quinshad Davis2016North Carolina17.4-0.8121.6-10.18
Bralon Addison2016OregonYES23.9-0.222.2-0.330.13
Keyarris Garrett2016TulsaYES36.70.9923.30.870.13
Sterling Shepard2016OklahomaYES32.20.5722.90.450.12
Jamal Robinson2016UL Lafayette32.90.65230.530.11
Nelson Spruce2016ColoradoYES33.70.7123.10.650.06
Kenny Lawler2016CaliforniaYES14.6-1.0721.5-1.090.03
Cody Core2016Ole MissYES15.7-0.9721.7-0.88-0.09
Alex Erickson2016Wisconsin330.6523.20.74-0.09
Kolby Listenbee2016TCUYES17.9-0.7621.9-0.63-0.14
Donovan Harden2016Georgia State21.5-0.4322.3-0.2-0.22
K.J. Brent2016Wake Forest21.3-0.4422.4-0.1-0.34
Cayleb Jones2016ArizonaYES25.5-0.0522.80.32-0.37
Mose Frazier2016Memphis20-0.5722.3-0.18-0.39
Jemond Hazely2016San Diego State20.8-0.4922.4-0.06-0.43
Joe Hansley2016Colorado State14-1.1321.9-0.66-0.46
J.D. McKissic2016Arkansas State19.5-0.6122.4-0.13-0.48
Davonte Allen2016Marshall24.6-0.1322.80.37-0.5
Shaq Washington2016Cincinnati21-0.4722.60.07-0.54
Chris Moore2016CincinnatiYES20.8-0.4922.50.06-0.54
Jay Lee2016Baylor20.1-0.5522.50.02-0.57
Byron Marshall2016OregonYES12.6-1.2621.9-0.68-0.58
Darius Powe2016California11.4-1.3621.8-0.78-0.58
D.J. Foster2016Arizona StateYES15-1.0322.1-0.43-0.6
Macgarrett Kings Jr.2016Michigan State16.5-0.8922.3-0.26-0.63
Ryan Longoria2016Georgia Southern23.3-0.2622.90.44-0.7
Tevaun Smith2016Iowa23.6-0.2322.90.48-0.71
Durron Neal2016Oklahoma14-1.1322.2-0.37-0.76
Jordan Thompson2016West Virginia18-0.7522.50.01-0.76
Jakeem Grant2016Texas Tech25.1-0.0823.20.76-0.84
Paul Turner2016Louisiana Tech18.6-0.722.60.17-0.87
Devin Fuller2016UCLA9.4-1.5621.9-0.64-0.92
Simms McElfresh2016Appalachian State20.8-0.4922.90.5-0.98
Mekale McKay2016CincinnatiYES13.7-1.1622.4-0.09-1.06
T.J. Thorpe2016Virginia15.5-0.9822.60.12-1.1
Jarvis Bentley2016Troy17.1-0.8422.70.27-1.11
Tommylee Lewis2016Northern Illinois22.4-0.3423.20.78-1.11
Danny Anthrop2016Purdue15.1-1.0222.60.11-1.13
Dom Williams2016Washington State20.6-0.5123.10.63-1.14
Trevor Davis2016CaliforniaYES13.7-1.1522.50-1.15
Melvin Ray2016Auburn15.2-1.0122.70.22-1.23
Miles Shuler2016Northwestern9-1.5922.3-0.25-1.33
Alonzo Russell2016ToledoYES20.4-0.5323.30.86-1.39
Casey Martin2016Southern Mississippi20-0.5623.30.86-1.42
Antwane Grant2016Western Kentucky13.5-1.1822.70.25-1.43
Cameron Dickerson2016Northwestern6.8-1.822.2-0.3-1.5
Kenneth Scott2016Utah19.5-0.6123.30.89-1.5
DeAndre Reaves2016Marshall23.4-0.2423.71.32-1.56
Devon Cajuste2016StanfordYES14.3-
Gary Chambers2016Arizona State12.5-1.2622.80.34-1.6
Charone Peake2016ClemsonYES16.7-0.8723.20.8-1.68
Ryan Burbrink2016Bowling Green12.8-1.2422.90.49-1.73
Richard Mullaney2016Alabama11.4-1.3622.90.41-1.77
Braxton Miller2016Ohio StateYES13.9-1.1423.10.66-1.8
Autrey Golden2016Texas-El Paso7-1.7822.50.05-1.83
Ed'marques Batties2016MTSU25.9-0.0224.11.81-1.83
Stephen Anderson2016CaliforniaYES10.5-1.4522.90.48-1.92
D'haquille Williams2016AuburnYES19.1-0.6523.61.28-1.93
Danny Woodson II2016South Alabama15-1.0423.40.97-2
Chris Shillings2016Ball State10-1.522.90.51-2.01
Mitch Mathews2016Brigham Young19.1-0.6523.71.37-2.01
Maurice Harris2016California11.4-1.3723.10.73-2.09
Tevin Jones2016Memphis8.7-1.62230.62-2.24
Amir Carlisle2016Notre Dame11.2-1.3823.30.87-2.26
Bobo Beathard2016Appalachian State11.4-1.3723.30.91-2.28
Kyle Klein2016Kansas State21.8-0.424.21.9-2.29
Brandon Sheperd2016Oklahoma State8.4-1.6523.10.71-2.36
Max Morrison2016Cincinnati13.2-
Marvin Shinn2016South Alabama19.3-0.6324.11.77-2.4
Brandon Swindall2016Utah State9-1.5923.30.87-2.46
Jamal Turner2016Nebraska3.8-2.0822.90.48-2.56
Quenton Bundrage2016Iowa State20.2-0.5524.32.03-2.57
Pig Howard2016Tennessee2.2-2.2322.80.36-2.59
DeAnthony Arnett2016Michigan State9.8-1.5223.51.14-2.66
Jordan Fredrick2016Wisconsin6.2-1.8523.30.92-2.77
Joe Morrow2016Mississippi State5.7-1.923.30.94-2.84
KJ Myers2016West Virginia1.5-2.323.10.7-3
Von Pearson2016Tennessee16.9-0.8524.52.28-3.13
Bubba Poole2016Utah6.2-1.8523.71.41-3.26
Tres Houston2016Arkansas State22.8-0.325.33.12-3.42
Shamier Jeffery2016South Carolina8.7-1.6224.32.04-3.66


People frequently ask me how this class compares to recent years. To gain some perspective on that, here are the numbers of players from recent drafts who have a score over 2.47, which is the average score of the NFL’s top 12 receivers in 2015.

  • 2016 – 4 (Sharpe, P. Cooper, Boyd, Higgins)
  • 2015 – 4 (A. Cooper, Parker, Funchess, Strong)
  • 2014 – 8 (Robinson, Cooks, Matthews, Watkins, Evans, Richardson, Franklin, Landry)
  • 2013 – 3 (Hopkins, Allen, M. Wilson)
  • 2012 – 5 (Hill, Randle, Page, Jenkins, J. Gordon)

So, no, the 2016 class isn’t anywhere near the 2014 class, but it’s pretty close to the other receiving classes of the last five years.

Now to the players…

Tajae Sharpe first emerged in 2012 and has been nothing but phenomenal ever since. He’s pretty lean, and not overly athletic, but he had a great career and I think could pay off big for an NFL team willing to be patient with him.

Tyler Boyd and Rashard Higgins are eerily similar athletes, with similar Phenom Index scores and similar career trajectories. They aren’t perfect prospects, but they both posted elite seasons in 2014 and are athletic enough. I think they could really shine as the second option in a passing game after being so burdened to carry their collegiate offenses.

Maybe I go too far with the #JusticeForMikeThomas tweets, but you can see here why I feel so passionately about the Southern Miss alumnus. Although Mike Thomas wasn’t invited to the combine he posted a score better than 32 of the receivers who were invited. I think he should absolutely get drafted and will ultimately be a massive dynasty sleeper.

I’ll wait while you scroll through the results to find Josh Doctson, Michael Thomas (OSU) and Sterling Shepard. All three rank among the top eight receivers in the latest RotoViz Scouting Index, but posted scores lower than the NFL’s “worst” top-12 receiver, Doug Baldwin. It probably shouldn’t be a surprise that all three players are tremendously athletic, which might be propping up their status, but as Kevin Cole recently pointed out: collegiate receiver production isn’t everything, it’s the ONLY thing. Of the bunch, I’m most optimistic about Shepard because he was elite in 2014.

(JUNE 3 UPDATE: after a ton of research and contradictory evidence, Michael Thomas himself finally confirmed that he was born in 1994 and not 1993, thus improving his score dramatically from this original writing)

And say hello to Braxton Miller for me, if you can find him. I have serious doubts about him as a receiver.

If you want to leave a comment, you are welcomed to do so, but please be civil. After all, it’s just fantasy football.

Jon Moore is a contributor at RotoViz and a cohost of Rotoviz Radio – A Fantasy Football Podcast. Continue this conversation with him on Google+Facebook or Twitter.

  1. for the NFL’s top performers in 2014  (back)
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